Application

Now that you have completed all of the activities in this chapter, use the concepts and techniques that you've learned to respond to these questions. Be sure to examine the data to check the conditions for inference, and explain which technique you used, why you chose it, and what you conclude.

  1. Scenario: Let's continue analyzing the data for adults in the NHANES data table. For each of the following columns, estimate the difference between the male and female respondents using a 95% confidence level.

    1. What is the estimated difference in Body Mass Index (BMI)?

    2. What is the estimated difference in systolic blood pressure?

    3. What is the estimated difference in diastolic blood pressure?

    4. What is the estimated difference in waist circumference?

  2. Scenario: We'll continue our analysis of the pipeline disruption data in the Southern and Southwestern regions. The columns PRPTY and GASPRP contain the dollar value of property and natural gas lost as a consequence of the disruption.

    1. Report and interpret a 95% confidence interval for the difference in mean property value costs of a pipeline disruption.

    2. Test the hypothesis that there is no difference in the mean natural gas loss costs between the two regions.

  3. Scenario: Go back to the full Pipeline Safety data table. Exclude and hide all incidents except those involving LEAKS and RUPTURES of pipelines.

    1. Does it take longer, on average, to secure the area after a rupture than after a leak?

    2. Estimate the difference in property damage costs associated with leak versus ruptures.

    3. Test the hypothesis that the variances are equal in comparing gas loss costs for leaks versus ruptures. Explain your conclusion.

  4. Scenario: Parkinson's disease (PD) is a neurological disorder affecting millions of older adults around the world. Among the common symptoms are tremors, loss of balance, and difficulty in initiating movement. Other symptoms include vocal impairment. We have a data table, Parkinsons (Little, McSharry, Hunter, and Ramig, 2008), containing a number of vocal measurements from a sample of 32 patients, 24 of whom have PD.

    Vocal measurement usually involves having the patient read a standard paragraph or sustain a vowel sound or do both. Two common measurements of a patient's voice refer to the wave form of sound: technicians note variation in the amplitude (volume) and frequency (pitch) of the voice. In this scenario, we will focus on just three measurements.

    • MDVP:F0(Hz) – vocal fundamental frequency (baseline measure of pitch)

    • MDVP:Jitter(Abs) – jitter refers to variation in pitch

    • MDVP:Shimmer(db) – shimmer refers to variation in volume

    1. Examine the distributions of these three columns, distinguishing between patients with and without PD. Do these data meet the conditions for running and interpreting a two-sample t-test? Explain your thinking.

    2. Use an appropriate technique to decide whether PD and non-PD patients have significantly different baseline pitch measurements.

    3. Use an appropriate technique to decide whether PD and non-PD patients have significantly different jitter measurements.

    4. Use an appropriate technique to decide whether PD and non-PD patients have significantly different shimmer measurements.

  5. Scenario: The data table Airline Delays contains a sample of flights for two airlines destined for four busy airports. Our goal is to analyze the delay times, expressed in minutes, and compare the two airlines.

    1. Assume this is an SRS of many flights by the selected carrier over a long period of time. Is the variance of delay the same for both airlines?

    2. What can you conclude about the difference in mean delays for these two airlines?

  6. Scenario: Let's look again at the TimeUse data. For each of the following questions, evaluate the extent to which conditions for inference have been met, and then report on what you find when you use an appropriate technique.

    1. Estimate the mean difference in the amount of time men and women spent sleeping in 2003.

    2. Estimate the mean difference in time that individuals devoted to e-mail in 2003 versus 2007.

    3. What can you conclude about the difference in the mean amount of time spent by women and men socializing on a given day?

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